A Modified Outlier Detection Method in Dynamic Data Reconciliation

Data reconciliation technology can decrease the level of corruption of process data due to measurement noise, but the presence of outliers caused by process peaks or unmeasured disturbances will smear the reconciled results. Based on the analysis of limitation of conventional outlier detection algorithms, a modified outlier detection method in dynamic data reconciliation (DDR) is proposed in this paper. In the modified method, the outliers of each variable are distinguished individually and the weight is modified accordingly. Therefore, the modified method can use more information of normal data, and can efficiently decrease the effect of outliers. Simulation of a continuous stirred tank reactor (CSTR) process verifies the effectiveness of the proposed algorithm.

Chaotic system and QR factorization based robust digital image watermarking algorithm

In order to protect copyright of digital images,a new robust digital image watermarking algorithm based on chaotic system and QR factorization was proposed.The host images were firstly divided into blocks with same size,then QR factorization was performed on each block.Pseudorandom circular chain(PCC) generated by logistic mapping(LM) was applied to select the embedding blocks for enhancing the security of the scheme.The first column coefficients in Q matrix of chosen blocks were modified to embed watermarks without causing noticeable artifacts.Watermark extraction procedure was performed without the original cover image.The experimental results demonstrate that the watermarked images have good visual quality and this scheme is better than the existing techniques,especially when the image is attacked by cropping,noise pollution and so on.Analysis and discussion on robustness and security issues were also presented.

A robust multi-objective and multi-physics optimization of multi-physics behavior of microstructure

A new strategy is presented to solve robust multi-physics multi-objective optimization problem known as improved multi-objective collaborative optimization （IMOCO） and its extension improved multi-objective robust collaborative （IMORCO）. In this work, the proposed IMORCO approach combined the IMOCO method, the worst possible point （WPP） constraint cuts and the Genetic algorithm NSGA-II type as an optimizer in order to solve the robust optimization problem of multi-physics of microstructures with uncertainties. The optimization problem is hierarchically decomposed into two levels： a microstructure level, and a disciplines levels, For validation purposes, two examples were selected： a numerical example, and an engineering example of capacitive micro machined ultrasonic transducers （CMUT） type. The obtained results are compared with those obtained from robust non-distributed and distributed optimization approach, non-distributed multi-objective robust optimization （NDMORO） and multi-objective collaborative robust optimization （McRO）, respectively. Results obtained from the application of the IMOCO approach to an optimization problem of a CMUT cell have reduced the CPU time by 44% ensuring a Pareto front close to the reference non-distributed multi-objective optimization （NDMO） approach （mahalanobis distance, D2M =0.9503 and overall spread, So=0.2309）. In addition, the consideration of robustness in IMORCO approach applied to a CMUT cell of optimization problem under interval uncertainty has reduced the CPU time by 23% keeping a robust Pareto front overlaps with that obtained by the robust NDMORO approach （D2M =10.3869 and So=0.0537）.

A novel wireless personal area network technology: ultra wide band technology

Ultra Wideband (UWB) technology is promising for wireless personal area network (WPAN) applications due to its high data rate, low power requirement and short-range characteristics. Instead of exploring new unused frequency band, the UWB communication follows the overlay principle, i.e., sharing the spectrum with existing systems and devices. This novel radio technology has been recently approved by the regulatory authorities in the United States and Canada, and is being considered for approval in Europe and Asia. In this paper, an overview of the UWB radio technology from the technical, economical, and regulatory perspectives is provided. Firstly, the definition of UWB by the Federal Communications Commission (FCC) is introduced, followed by a brief introduction to the history. The current status of the standardization process resulting from the FCC’s recent decision to permit unlicensed operation in the [3.1 - 10.6] GHz band is discussed. Then, the reasons of considering UWB as a future solution for WLAN/WPAN applications are studied. In particular, the unique properties of UWB and its difference from other wireless technology alternatives are studied. Then, the benefits and challenges related to the commercial deployment of UWB for future applications are discussed. Finally, the research problems and challenges posed by the UWB technology are focused.

A Locking-free Nonconforming Finite Element for Planar Linear Elasticity

We propose a locking-free nonconforming finite element method to solve for the displacement variation in the pure displacement boundary value problem of planar linear elasticity. The method proposed in this paper is robust and optimal, in the sense that the convergence estimate in the energy is independent of the Lame parameter λ.

古代的“橡皮”

在纸发明以前，古人的书写材料，主要是以丝织成的帛和用竹木制成的简牍。《墨子》的《尚贤》《兼爱》《非攻》《天志》《明鬼》《非命》《责义》以及《鲁问》诸篇中，每每提到“书于竹帛”或“书之竹帛”。

Robust estimation in inverse problems via quantile coupling

In this article we consider a sequence of hierarchical space model of inverse problems.The underlying function is estimated from indirect observations over a variety of error distributions including those that are heavy-tailed and may not even possess variances or means.The main contribution of this paper is that we establish some oracle inequalities for the inverse problems by using quantile coupling technique that gives a tight bound for the quantile coupling between an arbitrary sample p-quantile and a normal variable,and an automatic selection principle for the nonrandom filters.This leads to the data-driven choice of weights.We also give an algorithm for its implementation.The quantile coupling inequality developed in this paper is of independent interest,because it includes the median coupling inequality in literature as a special case.

ROBUST OUTPUT FEEDBACK STABILIZATION OF NONLINEAR NETWORKED SYSTEMS VIA A FINITE DATA-RATE COMMUNICATION CHANNEL

This paper addresses a robust stabilization problem of a class of uncertain nonlinear systems using output measurements via a finite data-rate communication channel. The authors assumes that there exist an observer and a control law for the systems in the absence of any finite data-rate communi- cation channel. Based on the observer and the control law, the authors constructs an encoder/decoder pair and provides a sufficient condition, including suitable sampling period and data rate, which will guarantee the stability of the closed-loop systems when a finite data-rate communication channel is introduced.

Three Paradigms in Lu Xun Research and Contemporary Value Options

Research on Lu Xun is never simply the analysis of an individual writer, but constitutes an understanding of the cultural attributes represented by Lu Xun himself and his writings. Likewise, the evaluation of research on Lu Xun is never a simple evaluation of academic history, but rather a social evaluation associated with the value orientations of those times. At present, with the return of academic logic and the growing tendency toward private research, a noteworthy divergence of standpoints and evaluations of Lu Xun research has emerged. At the same time, as a prominent discipline that has been over-interpreted, research on Lu Xun is demonstrating a tendency toward redundancy and triviality. Three fundamental paradigms are commonly employed in research on Lu Xun： historical research that attempts to explore historical materials; academic research that focuses on knowledge interpretation and aesthetic evaluation; and contemporary research that pursues the contemporary meaning and values of Lu Xun＇s ideas. Each paradigm offers an insight into and understanding of Lu Xun＇s rich and complex spiritual world; each presents a paradox of one kind or the other; and each performs different value functions.

Variable Selection for Structural Equation with Endogeneity

This paper studies variable selection problem in structural equation of a two-stage least squares （2SLS） model in presence of endogeneity which is commonly encountered in empirical economic studies. Model uncertainty and variable selection in the structural equation is an important issue as described in Andrews and Lu （2001） and Caner （2009）. The authors propose an adaptive Lasso 2SLS estimator for linear structural equation with endogeneity and show that it enjoys the oracle properties, i.e., the consistency in both estimation and model selection. In Monte Carlo simulations, the authors demonstrate that the proposed estimator has smaller bias and MSE compared with the bridge-type GMM estimator （Caner, 2009）. In a case study, the authors revisit the classic returns to education problem （Angrist and Krueger, 1991） using the China Population census data. The authors find that the education level not only has strong effects on income but also shows heterogeneity in different age cohorts.

Robust flutter analysis based on genetic algorithm

Robust flutter analysis considering model uncertain parameters is very important in theory and engineering applications.Modern robust flutter solution based on structured singular value subject to real parametric uncertainties may become difficult because the discontinuity and increasing complexity in real mu analysis.It is crucial to solve the worst-case flutter speed accurately and efficiently for real parametric uncertainties.In this paper,robust flutter analysis is formulated as a nonlinear programming problem.With proper nonlinear programming technique and classical flutter analysis method,the worst-case parametric perturbations and the robust flutter solution will be captured by optimization approach.In the derived nonlinear programming problem,the parametric uncertainties are taken as design variables bounded with perturbed intervals,while the flutter speed is selected as the objective function.This model is optimized by the genetic algorithm with promising global optimum performance.The present approach avoids calculating purely real mu and makes robust flutter analysis a plain job.It is illustrated by a special test case that the robust flutter results coincide well with the exhaustive method.It is also demonstrated that the present method can solve the match-point robust flutter solution under constant Mach number accurately and efficiently.This method is implemented in problem with more uncertain parameters and asymmetric perturbation interval.

A WEIGHTED PRODUCT METHOD FOR BIDDING STRATEGIES IN MULTI-ATTRIBUTE AUCTIONS

To eliminate computational problems involved in evaluating multi-attribute bids with differentmeasures,this article first normalizes each individual component of a bid,and then makes use ofthe weighted product method to present a new scoring function that converts each bid into a score.Twokinds of multi-attribute auction models are introduced in terms of scoring rules and bidding objectivefunctions.Equilibrium bidding strategies,procurer's revenue comparisons and optimal auction designare characterized in these two models.Finally,this article discusses some improvement of robustnessof our models,with respect to the assumptions.

Matrix perturbation based approach for sensitivity analysis of eigen-solutions in a microgrid

Sensitivities of eigen-solutions to control variables play an important role in microgrid studies,such as coordinated optimal design of controllers and parameters,robust stability analysis on control variables,oscillation modes analysis on a system,etc.Considering the importance of sensitivities and the complexity of state matrix in a microgrid,parameter perturbations are utilized in this paper to analyze the construction characteristics of state matrix.Then,the sensitivities of eigenvalues and eigenvectors to control variables are obtained based on the first-order matrix perturbation theory,which makes the complex derivations of sensitivity formulas and repeated solutions of eigenvalue problem unnecessary.Finally,the effectiveness of the matrix perturbation based approach for sensitivity calculation in a microgrid is verified by a numerical example on a low-voltage microgrid prototype.